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Measuring systemic risk in the Korean banking sector via dynamic conditional correlation models

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Frame of Image ac.kr ** Economist, Systemic Risk Analysis Team, Marcroprudential Analysis Department, the Bank of Korea, 39, Namdaemunno 3-Ga, Jung-Gu, Seoul 100-794, Republic of Korea, Email: hjmoon@bok.or.kr The authors especially thank Tae Soo Kang, Byung Hee Sung, Seung Hwan Lee and seminar participants at the Bank of Korea for their useful comments and suggestions. Professor Yun acknowledges the financial support and hospitality of the Bank of Korea. All remaining errors are our own.
Contents
Ⅰ . Introduction ··············································································· 1 Ⅱ . Literature Review ····································································· 3 Ⅲ . Methodology ············································································· 6
1. MES ············································································································ 6 2. CoVaR ········································································································ 9
Ⅳ . Empirical Results ····································································· 11
1. Data ········································································································ 11 2. Estimation Results of the DCC Models ············································· 12 3. Systemic Risk Contributions of Individual Banks ···························· 15 4. Aggregate Systemic Risk Measures ··················································· 25
Ⅴ . Conclusions


Full Text
Title Measuring systemic risk in the Korean banking sector via dynamic conditional correlation models
Similar Titles
Material Type Reports
Author(English)

Yun, Jaeho; Moon, Hyejung

Publisher

[Seoul]:The Bank of Korea

Date 2013-12
Series Title; No BOK Working Paper
Pages 38
Subject Country South Korea(Asia and Pacific)
Language English
File Type Documents
Original Format pdf
Subject Economy < Financial Policy
Holding The Bank of Korea; KDI School

Abstract

In this paper we study systemic risks in the Korean banking sector by using two famous systemic risk measures – the MES (marginal expected shortfall) and CoVaR. To compute both measures we employ Engle's dynamic conditional correlation model. Our empirical analysis shows, first, that although these two systemic risk measures differ in defining the contributions to systemic risk, both are qualitatively very similar in explaining the cross-sectional differences in systemic risk contributions across banks. Second, we find that systemic risk contributions are closely related to certain bank characteristic variables (e.g., VaR (value at risk), size and leverage ratio). However, there are differences between the cross-sectional and the time series dimensions in the effects of these variables. Last, using a threshold VAR model, we suggest an overall systemic risk measure – the aggregate MES – and its associated threshold value for use as an early warning indicator.